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Kategorie szczegółowe BISAC

Machine Learning: Theoretical Foundations and Practical Applications

ISBN-13: 9789813365179 / Angielski / Twarda / 2021 / 172 str.

Manjusha Pandey; Siddharth Swarup Rautaray
Machine Learning: Theoretical Foundations and Practical Applications Manjusha Pandey Siddharth Swarup Rautaray 9789813365179 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Machine Learning: Theoretical Foundations and Practical Applications

ISBN-13: 9789813365179 / Angielski / Twarda / 2021 / 172 str.

Manjusha Pandey; Siddharth Swarup Rautaray
cena 645,58 zł
(netto: 614,84 VAT:  5%)

Najniższa cena z 30 dni: 616,85 zł
Termin realizacji zamówienia:
ok. 22 dni roboczych
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inne wydania
Kategorie:
Technologie
Kategorie BISAC:
Technology & Engineering > Engineering (General)
Computers > Artificial Intelligence - General
Technology & Engineering > Telecommunications
Wydawca:
Springer
Seria wydawnicza:
Studies in Big Data
Język:
Angielski
ISBN-13:
9789813365179
Rok wydania:
2021
Wydanie:
2021
Numer serii:
000472346
Ilość stron:
172
Waga:
0.44 kg
Wymiary:
23.39 x 15.6 x 1.27
Oprawa:
Twarda
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

Chapter 1. What do RDMs capture in Brain Responses and Computational Models?.- Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems.- Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification.- Chapter 4. Applications of Machine learning in industry 4.0.- Chapter 5. Web Semantics and Knowledge Graph.- Chapter 6. Machine Learning based Wireless Sensor Networks.- Chapter 7. AI to Machine Learning:lifeless automation and Issues.- Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy.- Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.

Dr. Siddharth Swarup Rautary presently working as Associate Professor at the School of Computer Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India. He has teaching and research experience of more than 9 years. He did his doctoral degree from Indian Institute of Information Technology, Allahabad, U.P., India. His research interest includes big data analytics, image processing, intelligent systems, human–computer interaction and similar innovative areas. His research contribution includes 05 co-edited proceedings/books which include ASIC Springer series, more than 60 research publications in reputed conferences, book chapters and journals indexed in Scopus/SCI/ESCI and with a citation index of 1800 as on date. As an organizing chair, he has organized 05 international conferences (ICCAN2017, ICCAN 2019, 16th ICDCIT 2020, FICTA 2016, FICTA 2017) and has been part of different core committees of other conferences and workshops. He has delivered invited talks in different workshops and conferences. 

Dr. Manjusha Pandey presently working as Associate Professor at the School of Computer Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India. She has teaching and research experience of more than 9 years. She did her doctoral degree from Indian Institute of Information Technology, Allahabad, U.P., India; her research interest includes big data analytics, computer networks, intelligent systems, machine learning and similar innovative areas. Her research contribution includes 04 co-edited proceedings/books which include SIS Springer series, more than 65 research publications in reputed conferences, book chapters and journals indexed in Scopus/SCI/ESCI and with a citation index of 600 as on date. As an organizing chair, she has organized 02 international conferences and has been part of different core committees of other conferences and workshops. She has delivered invited talks in different workshops and conferences. 


This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9–12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms. 



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